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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Impact of the dynamical core on the direct simulation of tropical cyclones in a high-resolution global model

Our paper examines the impact of the dynamical core on the simulation of tropical cyclone (TC) frequency, distribution, and intensity. The dynamical core, the central fluid flow component of any general circulation model (GCM), is often overlooked in the analysis of a model's ability to simulate TCs compared to the impact of more commonly documented components (e.g., physical parameterizations). The Community Atmosphere Model version 5 is configured with multiple dynamics packages. This analysis demonstrates that the dynamical core has a significant impact on storm intensity and frequency, even in the presence of similar large-scale environments. In particular, the spectral element core produces stronger TCs and more hurricanes than the finite-volume core using very similar parameterization packages despite the latter having a slightly more favorable TC environment. Furthermore, these results suggest that more detailed investigations into the impact of the GCM dynamical core on TC climatology are needed to fully understand these uncertainties. Key Points The impact of the GCM dynamical core is often overlooked in TC assessments The CAM5 dynamical core has a significant impact on TC frequency and intensity A larger effort is needed to better understand this uncertainty

58 GEOSCIENCES↗
DOE OSTI2015

Short‐term time step convergence in a climate model

Abstract This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Improved Convection Parameterization with Detailed Aerosol–Cloud Microphysics for a Global Model

Abstract A new microphysical treatment that includes aerosol–cloud interactions and secondary ice production (SIP) mechanisms is implemented in the convection scheme of the Community Atmosphere Model, version 6 (CAM6). The approach is to embed a 1D Lagrangian parcel model in the bulk convective plume of the existing deep convection parameterization. Aerosol activation, growth processes including collision/coalescence, and three processes of SIP mechanisms, two of which are normally overlooked in atmospheric models, are represented in this embedded parcel model. These microphysical processes are treated with a hybrid bin/bulk scheme and a high spatial and temporal resolution for the integration of the embedded parcel in 1D, allowing vertical velocity to determine the microphysical evolution following the in-cloud motion during ascent. Simulations of an observed case (Midlatitude Continental Convective Clouds Experiment) of a mesoscale convective system in Oklahoma, United States, with a single-column model (SCAM) version of CAM, are compared with aircraft in situ and ground-based observations of microphysical properties from the convection and precipitation. Results from the validation show the new microphysical scheme has a good representation of the ice initiation in the bulk convective plume, including the known and empirically quantified pathways of primary and secondary initiation, with benefits for the accuracy of properties of its supercooled cloud liquid. The sensitivity simulations and use of tagging tracers for the validated simulation confirm that the newly included SIP mechanisms are of paramount importance for convective microphysics and can be successfully treated in the global model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Collaborative Project: High-resolution Global Modeling of the Effects of Subgrid-Scale Clouds and Turbulence on Precipitating Cloud Systems

We proposed to implement, test, and evaluate recently developed turbulence parameterizations, using a wide variety of methods and modeling frameworks together with observations including ARM data. We have successfully tested three different turbulence parameterizations in versions of the Community Atmosphere Model: CLUBB, SHOC, and IPHOC. All three produce significant improvements in the simulated climate. CLUBB will be used in CAM6, and also in ACME. SHOC is being tested in the NCEP forecast model. In addition, we have achieved a better understanding of the strengths and limitations of the PDF-based parameterizations of turbulence and convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The E3SM version 1 single-column model

Abstract. The single-column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM) but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to “replay” a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long-standing biases in the full GCM runs while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Performance of Goddard Earth Observing System GCM Column Radiation Models under Heterogeneous Cloud Conditions

We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.

Oreopoulos, L.↗
DOE OSTI2015

The effect of large-scale model time step and multiscale coupling frequency on cloud climatology, vertical structure, and rainfall extremes in a superparameterized GCM

The effect of global climate model (GCM) time step—which also controls how frequently global and embedded cloud resolving scales are coupled—is examined in the Superparameterized Community Atmosphere Model ver 3.0. Systematic bias reductions of time-mean shortwave cloud forcing (~10 W/m 2 ) and longwave cloud forcing (~5 W/m 2 ) occur as scale coupling frequency increases, but with systematically increasing rainfall variance and extremes throughout the tropics. An overarching change in the vertical structure of deep tropical convection, favoring more bottom-heavy deep convection as a global model time step is reduced may help orchestrate these responses. The weak temperature gradient approximation is more faithfully satisfied when a high scale coupling frequency (a short global model time step) is used. These findings are distinct from the global model time step sensitivities of conventionally parameterized GCMs and have implications for understanding emergent behaviors of multiscale deep convective organization in superparameterized GCMs. Lastly, the results may also be useful for helping to tune them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which the atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH 4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH 4 concentration gradients and growth rates. In conclusion, this study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH 4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models

We use observations of robust scaling behavior in clouds and precipitation to derive constraints on how partitioning of precipitation should change with model resolution. Our analysis indicates that 90-99% of stratiform precipitation should occur in clouds that are resolvable by contemporary climate models (e.g., with 200 km or finer grid spacing). Furthermore, this resolved fraction of stratiform precipitation should increase sharply with resolution, such that effectively all stratiform precipitation should be resolvable above scales of ~50 km. We show that the Community Atmosphere Model (CAM) and the Weather Research and Forecasting (WRF) model also exhibit the robust cloud and precipitation scaling behavior that is present in observations, yet the resolved fraction of stratiform precipitation actually decreases with increasing model resolution. A suite of experiments with multiple dynamical cores provides strong evidence that this `scale-incognizant' behavior originates in one of the CAM4 parameterizations. An additional set of sensitivity experiments rules out both convection parameterizations, and by a process of elimination these results implicate the stratiform cloud and precipitation parameterization. Tests with the CAM5 physics package show improvements in the resolution-dependence of resolved cloud fraction and resolved stratiform precipitation fraction.

atmospheric↗
DOE OSTI2018

Modeling East Asian Dust and Its Radiative Feedbacks in CAM4-BAM

East Asian dust and its radiative feedbacks are analyzed by the use of the fourth version of the Community Atmosphere Model (CAM4) with a bulk aerosol model parameterization (BAM) for the dust size distribution (CAM4-BAM). Two numerical experiments are conducted and intercompared: one with (Active) and one without (Passive) the radiative effects of dust aerosols. This CAM4-BAM captures the main spatial distribution of the dust aerosol optical depth (AOD) and the dust surface concentrations over East Asia, with positive correlations with the local observational data on annual and seasonal means. A comparative analysis of the Active and Passive experiments reveals that consideration of the dust-radiation interaction can significantly reduce dust emissions, loading, transport, and dry and wet depositions over East Asia, which is opposite to the enhanced dust cycle over North Africa. Further analysis of the contrasting dust-radiation feedbacks between North Africa and East Asia shows that over North Africa, the dust radiative forcing significantly increases the surface temperature and 10-m wind speed, whereas it decreases the surface temperature and the surface wind speeds over East Asia. These contrasting radiative effects, in turn, result in distinct dust cycle changes over these two regions. Thus, mechanistic analysis reveals that the radiative contrasts between East Asia and North Africa are mainly due to the differences in their regional surface albedo, dust vertical distribution and size distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Impact of tropical cyclones on modeled extreme wind-wave climate

Here, the effect of forcing wind resolution on the extremes of global wind-wave climate are investigated in numerical simulations. Forcing winds from the Community Atmosphere Model at horizontal resolutions of ~1.0° and ~0.25° are used to drive Wavewatch III. Differences in extreme wave height are found to manifest most strongly in tropical cyclone (TC) regions, emphasizing the need for high-resolution forcing in those areas. Comparison with observations typically show improvement in performance with increased forcing resolution, with a strong influence in the tail of the distribution, although simulated extremes can exceed observations. A simulation for the end of the 21st century under a RCP 8.5 type emission scenario suggests further increases in extreme wave height in TC regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Final DOE-ASR Report for the Project “Advancing our Understanding and the Remote Sensing of Ice Clouds”

This project has evolved during its execution, and what follows are the key project findings. This project has arguably provided the first global view of how cirrus cloud (defined as having cloud base temperature T < 235 K) nucleation physics (evaluated through satellite retrievals of ice particle number concentration Ni, effective diameter De and ice water content IWC) evolves with the seasons for a given temperature, latitude zone and surface type (e.g. ocean vs. land), based on a new satellite remote sensing method developed for this project. The retrieval method is unique in that it is very sensitive to the small ice crystals that govern the number concentration Ni, allowing Ni to be retrieved. The method currently samples single-layer cirrus clouds having visible optical depth ranging from about 0.3 to 3.0, using co-located observations from the Infrared Imaging Radiometer (IIR) and from the CALIOP (Cloud and Aerosol Lidar with Orthogonal Polarization) lidar aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) polar orbiting satellite, employing IIR channels at 10.6 μm and 12.05 μm. Retrievals of Ni are primarily used to estimate the cirrus cloud formation mechanism; that is, either homo- or heterogeneous ice nucleation (henceforth hom and het). This is possible since, in general, hom produces more than an order of magnitude more ice crystals than does het. Thus the retrievals provide insight on how these mechanisms change with the seasons for a given latitude zone or region, based on the years 2008 and 2013. Using a conservative criterion for hom cirrus, on average, the sampled cirrus clouds formed through hom occur about 43% of the time in the Arctic and 50% of the time in the Antarctic, and during winter at mid-latitudes in the Northern Hemisphere, hom cirrus occur 37% of the time. Elsewhere (and during other seasons in the Northern Hemisphere mid-latitudes), this hom cirrus fraction is lower, and it is lowest in the tropics. Thus, the microphysical properties of cirrus clouds in the Polar Regions are much different than they are in the tropics; something unknown prior to this study. Moreover, the frequency of cirrus cloud occurrence in the Polar Regions varies strongly with season, peaking during winter in the Arctic and during spring in the Antarctic. Considering these seasonal changes in microphysics and inferred cloud coverage, this leads us to speculate that the buildup of Arctic cirrus during winter may significantly contribute to tropospheric heating in that region, possibly affecting winter jet-stream dynamics and mid-latitude weather patterns through the thermal-wind balance relationship. This cirrus cloud research provides essential guidance for realistically representing cirrus clouds in climate models; guidance previously unavailable. For example, mid-latitude hom cirrus were widespread during winter over or nearby mountainous terrain, evidently due to mountain-induced waves that produce strong updrafts at cirrus cloud levels. The treatment of turbulent mountain stress and gravity waves will likely need to be improved in climate models in order to adequately represent cirrus clouds outside the tropics. Another goal of this project was to develop a ground-based 94-GHz radar retrieval for winter snowstorms, based on (1) an improved analytical framework describing the interaction of radiation from radar with snowfall and (2) the development of a steady-state snow growth model that predicts the height-evolution of the ice particle size distribution through ice particle growth by vapor diffusion, aggregation and riming (i.e. the growth of snow through collisions with supercooled cloud droplets). Although activities (1) and (2) were completed, there was insufficient time to test and finalize the radar retrieval scheme. However, activity (2) provided a new method for relating ice particle mass “m” and projected area “A” to the ice particle maximum dimension “D”. The ice cloud microphysical processes (which determine ice cloud radiative properties) in climate models are parameterized in terms of these m-D and A-D relationships. By improving these relationships, the ice cloud radiative properties in Community Atmosphere Model version 5, or CAM5 (an atmosphere global climate model, or GCM) were improved. Student funding from the University of Nevada, Reno, was combined with funds from this project to conduct some basic research on the mechanism of the North American monsoon, or NAM. Federal research on the NAM has dwindled since 2006, but atmospheric soundings taken during research vessel cruises in the Gulf of California (GC) during the North American Monsoon Experiment (NAME) were used to reveal a likely mechanism that explains the relationship between an intrusion of tropical warm water into the GC during late spring-early summer and the onset of relatively heavy NAM rainfall in northwest Mexico and the southwestern United States. These soundings, combined with reanalysis data, satellite sea surface temperatures and satellite measurements of outgoing longwave radiation were used to develop and provide evidence for a planetary-scale NAM mechanism. As far as we know, no other physical explanation has been offered for the spring-summer evolution of the NAM system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

On the relationships among cloud cover, mixed‐phase partitioning, and planetary albedo in GCMs

Abstract In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean‐state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed‐phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed‐phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water would also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti‐correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti‐correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature‐dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble.

58 GEOSCIENCES↗
DOE OSTI2018

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2 , respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Aquaplanets as a Framework for Examination of Aerosol Effects

Although fundamental to the planetary radiative balance, aerosol impacts are highly uncertain in climate simulations because of the uneven distribution of aerosol sources and the complex interactions with radiation and clouds that are difficult to represent in climate models. This study proposes that aquaplanet configurations represent an idealized framework to investigate aerosol effects. As a simple demonstration, a series of aquaplanet simulations with the Community Atmosphere Model version 6 shows that the spatial distribution of aerosol emissions changes the aerosol effective radiative forcing even with unchanged total emissions. Some statistical properties of the simulations are presented to show that relatively short model integrations yield robust results. Much of the aerosol effect is shown to arise from aerosol–cloud interactions, especially through rapid adjustments associated with the aerosol lifetime effect that alter the cloud optical thickness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Understanding cloud droplet spectral dispersion effect using empirical and semi-analytical parameterizations in NCAR CAM5.3

Five parameterizations of cloud droplet spectral shape are implemented in a global climate model to investigate the dispersion effect and aerosol indirect effect (AIE). We design a series of experiments by modifying the microphysical cloud scheme of NCAR CAM5.3 (Community Atmospheric Model Version 5.3). We employ four empirical (Martin94, RLiu03, PengL03, Liu08) and one semi-analytical (LiuLi15) expressions for cloud droplet spectral shape parameters. Analysis focuses on the instantaneous differences in the simulated cloud microphysical properties and the comparison between model output and satellite data. The results show that RLiu03, PengL03 and LiuLi15 produce wider droplet spectrum and faster autoconversion rate, but Liu08 has a narrower droplet spectrum and slower autoconversion rate than the default parameterization (Martin94) in CAM5.3. Global dispersion effects caused by the five parameterizations modify the aerosol indirect effect by -10% (counteract) to 13% (strengthen). The simulated AIEs and dispersion effects exhibit noticeably spatial inhomogeneity. In the sensitive regions of AIE (Southeast Asia, North Pacific and west coast of South America), we decompose the response of shortwave cloud forcing to the change in droplet number for analysis. The varying dispersion effects can be explained by different responses of cloud properties in different spectral parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Quantifying uncertainty from aerosol and atmospheric parameters and their impact on climate sensitivity

Abstract. Climate sensitivity in Earth system models (ESMs) is an emergentproperty that is affected by structural (missing or inaccurate model physics)and parametric (variations in model parameters) uncertainty. This workprovides the first quantitative assessment of the role of compensationbetween uncertainties in aerosol forcing and atmospheric parameters, andtheir impact on the climate sensitivity of the Community Atmosphere Model,Version 4 (CAM4). Running the model with prescribed ocean and ice conditions,we perturb four parameters related to sulfate and black carbon aerosolradiative forcing and distribution, as well as five atmospheric parametersrelated to clouds, convection, and radiative flux. In this experimental setupwhere aerosols do not affect the properties of clouds, the atmosphericparameters explain the majority of variance in climate sensitivity, with twoparameters being the most important: one controlling low cloud amount, andone controlling the timescale for deep convection. Although the aerosolparameters strongly affect aerosol optical depth, their impacts on climatesensitivity are substantially weaker than the impacts of the atmosphericparameters, but this result may depend on whether aerosol–cloud interactionsare simulated. Based on comparisons to inter-model spread of other ESMs, weconclude that structural uncertainties in this configuration of CAM4 likelycontribute 3 times more to uncertainty in climate sensitivity thanparametric uncertainties. We provide several parameter sets that couldprovide plausible (measured by a skill score) configurations of CAM4, butwith different sulfate aerosol radiative forcing, black carbon radiativeforcing, and climate sensitivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemble forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.

58 GEOSCIENCES↗